Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/39014
Title: Development and applications of a sequential, minimal, radial basis function (RBF) neural network learning algorithm
Authors: Lu, Ying Wei.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 1997
Abstract: This thesis presents a new sequential learning algorithm for realizing a minimal Radial Basis Function (RBF) neural network, referred to as M-RAN (Minimal Resource Allocation Network). Unlike most of the classical RBF neural networks with the number of hidden neurons fixed apriori, the network structure is dynamic in the proposed M-RAN algorithm.
URI: http://hdl.handle.net/10356/39014
Rights: NANYANG TECHNOLOGICAL UNIVERSITY
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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